SoroushVahidi/scidocs huggingface dataset:
Correlated Nonideal Effects of Dark and Light I–V Characteristics in a-Si/c-Si Heterojunction Solar Cells
(2014)

a-Si/c-Si (amorphous Silcon/crystalline Silicon) heterojunction solar cells exhibit several distinctive dark and light I-V nonideal features. The dark I-V of these cells exhibits unusually high ideality factors at low forward-bias and the occurrence of a “knee” at medium forward-bias. Nonidealities under illumination, such as the failure of superposition and the occurrence of an “S-type” curve, are also reported in these cells. However, the origin of these nonidealities and how the dark I-V nonidealities manifest themselves under illumination, and vice versa, have not been clearly and consistently explained in the current literature. In this study, a numerical framework is used to interpret the origin of the dark I-V nonidealities, and a novel simulation technique is developed to separate the photo-current and the contact injection current components of the light I-V. Using this technique, the voltage dependence of photo-current is studied to explain the failure of the superposition principle and the origin of the S-type light I-V characteristics. The analysis provides a number of insights into the correlations between the dark I-V and the light I-V. Finally, using the experimental results from this study and from the current literature, it is shown that these nonideal effects indeed affect the dark I-V and the light I-V in a predictable manner.
Power Control in Ad-Hoc Networks: Theory, Architecture, Algorithm and Implementation of the COMPOW Protocol
(2002)

We present a new protocol for power control in ad hoc networks. We describe the issues in conceptualizing the power control problem, and provide an architecturally simple as well as theoretically well founded solution. The solution is shown to simultaneously satisfy the three objectives of maximizing the traffic carrying capacity of the entire network, extending battery life through providing low power routes, and reducing the contention at the MAC layer. Further, the protocol has the plug and play feature that it can be employed in conjunction with any routing protocol that pro-actively maintains a routing table. The protocol, called COMPOW, has been implemented in the Linux kernel and we describe the software architecture and implementation details.
Supervised Matrix Factorization for Cross-Modality Hashing
(2016)

Matrix factorization has been recently utilized for the task of multi-modal hashing for cross-modality visual search, where basis functions are learned to map data from different modalities to the same Hamming embedding. In this paper, we propose a novel cross-modality hashing algorithm termed Supervised Matrix Factorization Hashing (SMFH) which tackles the multi-modal hashing problem with a collective non-matrix factorization across the different modalities. In particular, SMFH employs a well-designed binary code learning algorithm to preserve the similarities among multi-modal original features through a graph regularization. At the same time, semantic labels, when available, are incorporated into the learning procedure. We conjecture that all these would facilitate to preserve the most relevant information during the binary quantization process, and hence improve the retrieval accuracy. We demonstrate the superior performance of SMFH on three cross-modality visual search benchmarks, i.e., the PASCAL-Sentence, Wiki, and NUS-WIDE, with quantitative comparison to various stateof-the-art methods [Kumar and Udupa, 2011; Rastegari et al., 2013; Zhang and Li, 2014; Ding et al., 2014].
Proposing a new design approach for M-learning applications
(2015)

As Information and Communication Technologies (ICT) are developing frequently, new learning approaches have been introduced to facilitate teaching and learning processes. Mobile devices are growing in popularity and there has been an increasing interest in their potential as innovative tools for learning. Mobile learning or shortly (M-learning) is a new learning approach intending to use mobile devices such as laptops, smart phones and personal digital assistant (PDA) in learning process in any place and at any time. M-learning application needs to be designed in a way that considers the special features and constraints of mobile devices such as screen size, available storage, processor speed and battery life. This paper explores the existing design approaches for M-learning and highlights their main limitations. As a step forward in this direction, this paper also proposes a new design approach for M-learning applications focusing mainly on three main aspects: learner, learning content and technology. The approach consists of three phases: starting dimensions (SD) phase, M-learning Development (MLD) phase and Learning Content Design (LCD) phase. Finally, this paper provides a case study scenario to demonstrate the feasibility of the proposed approach.
A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks
(2016)

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints on cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use mobile anchor nodes (MANs), which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. A considerable body of research has addressed the mobile anchor node assisted localization (MANAL) problem. However, to the best of our knowledge, no updated surveys on MAAL reflecting recent advances in the field have been presented in the past few years. This survey presents a review of the most successful MANAL algorithms, focusing on the achievements made in the past decade, and aims to become a starting point for researchers who are initiating their endeavors in MANAL research field. In addition, we seek to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful advances in this research field.
Coarse-to-Fine Question Answering for Long Documents
(2017)

We present a framework for question answering that can efficiently scale to longer documents while maintaining or even improving performance of state-ofthe-art models. While most successful approaches for reading comprehension rely on recurrent neural networks (RNNs), running them over long documents is prohibitively slow because it is difficult to parallelize over sequences. Inspired by how people first skim the document, identify relevant parts, and carefully read these parts to produce an answer, we combine a coarse, fast model for selecting relevant sentences and a more expensive RNN for producing the answer from those sentences. We treat sentence selection as a latent variable trained jointly from the answer only using reinforcement learning. Experiments demonstrate the state of the art performance on a challenging subset of the WIKIREADING dataset (Hewlett et al., 2016) and on a new dataset, while speeding up the model by 3.5x-6.7x.
Direct Causality Detection via the Transfer Entropy Approach
(2013)

The detection of direct causality, as opposed to indirect causality, is an important and challenging problem in root cause and hazard propagation analysis. Several methods provide effective solutions to this problem when linear relationships between variables are involved. For nonlinear relationships, currently only overall causality analysis can be conducted, but direct causality cannot be identified for such processes. In this paper, we describe a direct causality detection approach suitable for both linear and nonlinear connections. Based on an extension of the transfer entropy approach, a direct transfer entropy (DTE) concept is proposed to detect whether there is a direct information flow pathway from one variable to another. Especially, a differential direct transfer entropy concept is defined for continuous random variables, and a normalization method for the differential direct transfer entropy is presented to determine the connectivity strength of direct causality. The effectiveness of the proposed method is illustrated by several examples, including one experimental case study and one industrial case study.
From Adjective Glosses to Attribute Concepts: Learning Different Aspects That an Adjective Can Describe
(2015)

Adjectives are one of the major contributors to conveying subjective meaning to sentences. Understanding the semantics of adjectives is essential for understanding natural language sentences. In this paper we propose a novel approach for learning different properties that an adjective can describe, corresponding to the ‘attribute concepts’, which is not currently available in existing linguistic resources. We accomplish this by reading adjective glosses and bootstrapping attribute concepts from a seed of adjectives. We show that we can learn new attribute concepts using adjective glosses of WordNet adjectives with high accuracy as compared with human annotation on a test set.
Smart home garden irrigation system using Raspberry Pi
(2017)

Irrigation system is a method of allowing water to drip slowly to the roots of plants, either onto the soil surface or directly onto the root zone, through solenoid valve. However, it is found that the market price of the system is expensive for small area coverage. Thus, this paper proposes a design for smart home garden irrigation system that implements ready-to-use, energy-efficient, and cost effective devices. Raspberry Pi, which is implemented in this system is integrated with multi-sensors such as soil moisture sensors, ultrasonic sensors, and light sensors. This proposed system managed to reduce cost, minimize waste water, and reduce physical human interface. In this paper, the relay is utilized to control the switching of solenoid valve. The system also managed to measure moisture of the soil and control the solenoid valve according to human's requirements. It is conducted with Graphical User Interface (GUI) using Android application to activate watering activity. Email notification is also sent to the home user for alert purposes either for normal or critical operations. An experimental setup has been tested and it is proven that the system can intelligently control and monitor the soil moisture levels in the experiment field.
Achieving lightweight trustworthy traceability
(2014)

Despite the fact that traceability is a required element of almost all safety-critical software development processes, the trace data is often incomplete, inaccurate, redundant, conflicting, and outdated. As a result, it is neither trusted nor trustworthy. In this vision paper we propose a philosophical change in the traceability landscape which transforms traceability from a heavy-weight process producing untrusted trace links, to a light-weight results-oriented trustworthy solution. Current traceability practices which retard agility are cast away and replaced with a disciplined, just-in-time approach. The novelty of our solution lies in a clear separation of trusted trace links from untrusted ones, the change in perspective from `living-with' inacurate traces toward rigorous and ongoing debridement of stale links from the trusted pool, and the notion of synthesizing available `project exhaust' as evidence to systematically construct or reconstruct purposed, highly-focused trace links.
Instant Dehazing of Images Using Polarization
(2001)

We present an approach to easily remove the effects of haze from images. It is based on the fact that usually airlight scattered by atmospheric particles is partially polarized. Polarization filtering alone cannot remove the haze effects, except in restricted situations. Our method, however, works under a wide range of atmospheric and viewing conditions. We analyze the image formation process, taking into account polarization effects of atmospheric scattering. We then invert the process to enable the removal of haze from images. The method can be used with as few as two images taken through a polarizer at different orientations. This method works instantly, without relying on changes of weather conditions. We present experimental results of complete dehazing in far from ideal conditions for polarization filtering. We obtain a great improvement of scene contrast and correction of color. As a by product, the method also yields a range (depth) map of the scene, and information about properties of the atmospheric particles.
Types for Units-of-Measure: Theory and Practice
(2009)

Units-of-measure are to science what types are to programming. In science and engineering, dimensional and unit consistency provides a first check on the correctness of an equation or formula, just as in programming the passing of a program by the type-checker eliminates one possible reason for failure. Units-of-measure errors can have catastrophic consequences, the most famous of which was the loss in September 1999 of NASA’s Mars Climate Orbiter probe, caused by a confusion between newtons (the SI unit of force) and lbf (poundforce, a unit of force sometimes used in the US). The report into the disaster made many recommendations [14]. Notably absent, though, was any suggestion that programming languages might assist in the prevention of such errors, either through static analysis tools, or through type-checking. Over the years, many people have suggested ways of extending programming languages with support for static checking of units-of-measure. It’s even possible to abuse the rich type systems of existing languages such as C++ and Haskell to achieve it, but at some cost in usability [18, 6]. More recently, Sun’s design for its Fortress programming language has included type system support for dimensions and units [2]. In this short course, we’ll look at the design supported by the F# programming language, the internals of its type system, and the theoretical basis for units safety. The tutorial splits into three parts:
Programming languages and dimensions
(1995)

Scientists and engineers must ensure that the equations and formulae which they use are dimensionally consistent, but existing programming languages treat all numeric values as dimensionless. This thesis investigates the extension of programming languages to support the notion of physical dimension. A type system is presented similar to that of the programming language ML but extended with polymorphic dimension types. An algorithm which infers most general dimension types automatically is then described and proved correct. The semantics of the language is given by a translation into an explicitlytyped language in which dimensions are passed as arguments to functions. The operational semantics of this language is specified in the usual way by an evaluation relation defined by a set of rules. This is used to show that if a program is well-typed then no dimension errors can occur during its evaluation. More abstract properties of the language are investigated using a denotational semantics: these include a notion of invariance under changes in the units of measure used, analogous to parametricity in the polymorphic lambda calculus. Finally the dissertation is summarised and many possible directions for future research in dimension types and related type systems are described.
Development environments for autonomous mobile robots: A survey
(2007)

Robotic Development Environments (RDEs) have come to play an increasingly important role in robotics research in general, and for the development of architectures for mobile robots in particular. Yet, no systematic evaluation of available RDEs has been performed; establishing a comprehensive list of evaluation criteria targeted at robotics applications is desirable that can subsequently be used to compare their strengths and weaknesses. Moreover, there are no practical evaluations of the usability and impact of a large selection of RDEs that provides researchers with the information necessary to select an RDE most suited to their needs, nor identifies trends in RDE research that suggest directions for future RDE development. This survey addresses the above by selecting and describing nine open source, freely available RDEs for mobile robots, evaluating and comparing them from various points of view. First, based on previous work concerning agent systems, a conceptual framework of four broad categories is established, encompassing the characteristics and capabilities that an RDE supports. Then, a practical evaluation of RDE usability in designing, implementing, and executing robot architectures is presented. Finally, the impact of specific RDEs on the field of robotics is addressed by providing a list of published applications and research projects that give concrete examples of areas in which systems have been used. The comprehensive evaluation and comparison of the nine RDEs concludes with suggestions of how to use the results of this survey and a brief discussion of future trends in RDE design.
VQM-based QoS/QoE mapping for streaming video
(2010)

Numerous new broadband and multimedia applications have emerged in recent years, in which streaming video services are particularly of interest. Unlike data communication, streaming video requires a subjective measure of quality referred to as the Quality of Experience (QoE), but the subjective evaluation is very time consuming and complex. We are proposing an objective approach to provide mapping between QoE and Quality of Service (QoS), in which Video Quality Metric (VQM) is utilized to indicate QoE. We have analyzed the emulation results and derived a simple formula to estimate QoE from QoS parameters for streaming video under certain conditions. This method is non-intrusive and quick to use.
Nanoconnectomic upper bound on the variability of synaptic plasticity
(2015)

Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlation between size and efficacy of a synapse allowed us to estimate the variability of synaptic plasticity. In an EM reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites, having shared histories of presynaptic and postsynaptic activity. The spine heads and neck diameters, but not neck lengths, of these pairs were nearly identical in size. We found that there is a minimum of 26 distinguishable synaptic strengths, corresponding to storing 4.7 bits of information at each synapse. Because of stochastic variability of synaptic activation the observed precision requires averaging activity over several minutes.
Online Attendance Management System Using RFID with Object Counter
(2006)

Educational institutions’ administrators in our country and the whole world are concerned about regularity of student attendance. Student overall academic performance is affected by it. The conventional method of taking attendance by calling names or signing on paper is very time consuming, and hence inefficient. Radio Frequency Identification (RFID) based attendance system is one of the solutions to address this problem. A system that can automatically capture student’s attendance by flashing their student card at the RFID reader and save all the mentioned troubles was given by T.S.Lim et al. [1].The RFID system using web-based applications such as ASP.NET and IIS server to cater the recording and reporting of the students’ attendances was given by Abdul Aziz Mohammed et.al. [2]. Arulogun O. T. et al made an attempt to solve recurrent lecture attendance monitoring problem in developing countries using RFID technology [3]. Rajan Patel et al [4] presents the integration of ubiquitous computing systems into classroom for managing the students’ attendance using RFID technology. H.B. Hamid et al [5] gave a system that has been built using the web-based applications such as JSP, MySQL and Apache to cater the recording and reporting of the students’ attendances. NetBeans IDE 6.1 is used for developing the overall system. We have proposed the system in this paper using C#. Microsoft Visual Studio is used for the system designing. Also, the issue related to fake /false attendance through the RFID system has been addressed, we eliminate it by using a special object counter for the head count. Ankita Agrawal & Ashish Bansal 132
Model-based evaluation: from dependability to security
(2004)

The development of techniques for quantitative, model-based evaluation of computer system dependability has a long and rich history. A wide array of model-based evaluation techniques is now available, ranging from combinatorial methods, which are useful for quick, rough-cut analyses, to state-based methods, such as Markov reward models, and detailed, discrete-event simulation. The use of quantitative techniques for security evaluation is much less common, and has typically taken the form of formal analysis of small parts of an overall design, or experimental red team-based approaches. Alone, neither of these approaches is fully satisfactory, and we argue that there is much to be gained through the development of a sound model-based methodology for quantifying the security one can expect from a particular design. In this work, we survey existing model-based techniques for evaluating system dependability, and summarize how they are now being extended to evaluate system security. We find that many techniques from dependability evaluation can be applied in the security domain, but that significant challenges remain, largely due to fundamental differences between the accidental nature of the faults commonly assumed in dependability evaluation, and the intentional, human nature of cyber attacks.
The use of socially assistive robots in the design of intelligent cognitive therapies for people with dementia
(2009)

Currently the 2 percent growth rate for the world's older population exceeds the 1.2 rate for the world's population as a whole. By 2050, the number of individuals over the age 85 is projected to be three times more than there is today. Most of these individuals will need physical, emotional, and cognitive assistance. In this paper, we present a new adaptive robotic system based on the socially assistive robotics (SAR) technology that tries to provide a customized help protocol through motivation, encouragements, and companionship to users suffering from cognitive changes related to aging and/or Alzheimer's disease. Our results show that this approach can engage the patients and keep them interested in interacting with the robot, which, in turn, increases their positive behavior.